Understanding the Genetic Basis of Sex Differences in Human Height

Sex differences are prevalent across health, development and disease. Driven by the sex chromosomes, the largest source of genetic variation in the human population, trait differences between males and females can have important implications in treatment response and disease diagnosis. Genes along the X and Y chromosomes encode broadly-expressed regulators of the transcriptome and epigenome that have diverged in function and expression. These sex chromosome-linked gene pairs enforce differences in regulatory landscapes and autosomal gene expression patterns between biological males (XY) and females (XX), which can have far-reaching consequences. Despite this, the field of population genetics has rarely considered the special role of sex-linked loci and sex-biased genetic effectors in establishing sex-dependent trait variation. In this thesis, I integrate existing tools in statistical genetics for the repurposed goal of understanding the genetic basis of sex differences in complex traits. Through combining genome-wide association study (GWAS) data with gene expression panels and sex-biased gene expression information, previous work in the lab has demonstrated that genes with conserved sex bias contribute to the establishment of sex bias in height. First, to understand the relationship between GWAS power and sex differences, we compared the performance of two differently powered GWAS in their ability to explain sex bias in height, finding a modest increase in genetic insight by the larger GWAS. Second, we assessed functional elements across the genome that may differentially contribute to height between males and females to propose alternative mechanisms alongside gene expression that may establish sex differences in height. Altogether, the work presented in this thesis demonstrates the potential of sex differences research to utilize well-powered studies of sex-biased regulators and variant-trait associations to better understand the genetic mechanisms— including, but not limited, to gene expression— that cultivate and maintain sex differences in complex traits.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Aluru, Amulya S.

Advisor dc:contributor.advisor

• Page, David C.

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/156763

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/156763